42 articles in this selection

2009/12/23

With Christmas nearly upon us, I decided to go caroling through the blog archives of the DataFlux Community of Experts. After exhausting my singing voice, I selected my twelve personal favorites regarding the topics of data quality, data profiling, data governance, and master data management - otherwise known as The Twelve Days of Data....

2009/08/24

Articles describing five essential elements of MDM and CDI: a hub, data integration/middleware, data quality capabilities, external content and data governance.

2009/08/24

Several practitioners have contributed to this complex subject and have done a good job at describing the critical elements. There is one more element that's often overlooked however, and it remains a key differentiator and all too often, it's the difference between success and failure among the major initiatives I've had the opportunity to witness - modeling the blueprint for MDM....

2009/08/24

One of the more maddening things about new technology topics is how difficult it can be to pin down the basic facts, like how it is defined and what's the best approach. It's a bit like playing Scrabble without establishing a dictionary of record. Nobody knows for sure, but everybody has an opinion - and usually, they don't agree. It's very frustrating. I suggest Gartner amend its hype cycle to include this as a sixth phase - it could be called something like "The Mud Ditch of Confusion." Right now, I'm mired knee-deep in the mud with master data management. This post describes a few of the issues I'm trying to trudge through....

2009/08/24

Results of a survey on the use of Master Data Management within organizations and the different types of architectures that were employed.

2009/08/24

As companies have grown, so to have the number of systems that require access to each other's data. This is why data integration has become one of the largest custom development activities undertaken within an IT organization. It's rare that all systems (and their developers) integrate data the same way. While there may be rigor within an individual application or system, it's highly unlikely that all systems manipulate an individual subject area in a consistent fashion. This lack of integrity and consistency becomes visible when information on two different systems conflict. MDM isn't a silver bullet to address this problem. It is a method to address data problems one subject area at a time....

2009/08/21

List of challenges with regards to Customer Data.

2009/08/21

Data quality management and MDM are two key dimensions of enterprise information management. Despite the fact that industry treats them differently in terms of implementation approaches, methodologies and tools, a good amount of correlation and interdependencies exists between these two streams of EIM. Without DQM, MDM is merely a dump of the data repository, and sans MDM, DQM cannot bring ROI to the organization. In a true sense, DQM is the building block of an MDM hub, as quality and accurate data is key to the success of an MDM program. Let us not consign MDM to becoming another silo of data. MDM and DQM together create a strong fusion that supports the long term enterprise information management vision. Having decided on the subject areas/domains for MDM, it is imperative for an organization to launch a data discovery and analysis program. In-depth analysis of the quality and health of data is a prerequisite of the MDM program. The following data quality management steps are needed...

2009/08/06

DataCleaner is an Open Source application for profiling, validating and comparing data. These activities help you administer and monitor your data quality in order to ensure that your data is useful and applicable to your business situation. DataCleaner is the free alternative to software for master data management (MDM) methodologies, data warehousing (DW) projects, statistical research, preparation for extract-transform-load (ETL) activities and more....

2009/07/29

Master data management is used to improve the outcomes of an organization’s most critical business processes. By enabling organizations to optimize enterprise master data, MDM can help companies get the intended value out of these activities and tune them to become strategic differentiators. Most companies start to master data with a single domain, usually the data type they consider to be most critical to their success. For some, it is customer data. For others, it is product data. However, once their initial implementation is in place, companies soon realize they can achieve a significant increase in business benefits through mastering additional domains and the relationships between them....

2009/07/22

Get a short introduction to the Master Data Management Reference Architecture for the enterprise which supports implementing multiform Master Data Management (MDM). Learn about the key concepts that drive the design of the MDM Reference Architecture and Logical System Architecture and see how to map the relevant IBM Information Management software products to the core components of the Master Data Management Reference Architecture. Each product is briefly introduced, and in the Resources section of this paper you will find a wealth of additional information for reference. Finally, you will also learn about an upcoming book, Enterprise Master Data Management: An SOA Approach Managing Core Information, that describes the MDM Reference Architecture in full detail as well as other topics related to MDM....

2009/07/18

2009/07/18

In computing, master data management (MDM) comprises a set of processes and tools that consistently defines and manages the non-transactional data entities of an organization (also called reference data). MDM has the objective of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information....

2009/07/17

Most companies approach restructuring as a one-time-only activity in which an army of analysts tries to reconcile financial structures from organizational hierarchies, to budgets, to the accounts themselves. The fact is these activities aren't just part of high-profile M&A events. They occur every year as companies go through their annual budget processes. During a corporate restructuring the process usually takes longer than the acquisition itself....

2009/07/17

Why is there no simple, automated, or formalized, blue print for getting MDM going? Each and every enterprise starts their journey toward MDM, from a completely different place. As such, there is no single blue print, but several, even many. There are large patterns emerging, but these are today not detailed enough to provide individual blue print for each firm....

2009/07/17

InfoSphere MDM Server helps companies gain control over business information by enabling them to manage and maintain a complete and accurate view of their master data. InfoSphere MDM Server enables companies to extract maximum value from master data by centralizing multiple data domains and providing a comprehensive set of prebuilt business services that support a full range of master data management (MDM) functionality. This information center contains conceptual information to help you understand InfoSphere MDM Server and the ways that you can use it to solve your business problems, and provides valuable reference information that you may need to consult when you perform the tasks described....

2009/07/16

In this guest post by Peter Benson, the ISO 8000 Project Leader, we learn more about this new international data quality standard and how it could benefit data consumers and suppliers around the world.

2009/07/16

A new MDM vendor named DataQualityFirst seized on the Madoff scandal to offer a real-world example of how complex data management can be for businesses today and how a software solution can help understand and better manage the mess.

2009/07/16

Master Data Management (MDM) brings about two major challenges for companies: 1) Companies need to cope with the complexity of the subject, and 2) companies see themselves confronted with a wide range of IT products and solutions for MDM. Presenting a Functional Reference Architecture for Corporate Master Data Management, the present paper identifies and describes from a business perspective functional requirements MDM software should meet. The Functional Reference Architecture provides a basic terminology, a check list, and an assessment scheme for various application scenarios, like product evaluation, roadmap planning or exchange of information and experiences. Furthermore, MDM solutions of four software providers are examined with regard to their capability to meet the functions specified in the Functional Reference Architecture....

2009/07/16

ISO Standard for Master Data Quality: ISO/TS 8000-110:2008 specifies general, syntax, semantic encoding and data specification requirements for master data messages between organizations and systems. The focus of ISO/TS 8000-110:2008 is on requirements that can be checked by computer....

2009/07/16

A big list of articles on the cost of poor data quality.

2009/07/16

You probably don't think "data governance" is that important a topic. Especially when you've got IT budgetary fires raging or you're planning next week's layoffs. You may even think today's data management and master data management (MDM) and similar enterprisewide data governance initiatives are too complex. And crazy boring. That's OK. You're not totally wrong. But boring can be bountiful - as in saving corporate cash and increasing revenues....

2009/07/13

Gartner's seven building blocks of master data management (MDM) framework describe the essential elements that organizations need to address in an MDM program. Program managers should use this framework, and should ensure that their programs cover all MDM building blocks (customized as appropriate) to achieve success....

2009/07/13

What if you have five data intensive projects that are all in need of your very valuable resources for improving data quality? How do you decide where to focus? The choice is not always clear. Management may be interested in accurate reporting from your data warehouse, but revenue may be at stake in other projects. So, just how do you decide where to start?...

2009/07/13

In computing, master data management (MDM) comprises a set of processes and tools that consistently defines and manages the non-transactional data entities of an organization (also called reference data). MDM has the objective of providing processes for collecting, aggregating, matching, consolidating, quality-assuring, persisting and distributing such data throughout an organization to ensure consistency and control in the ongoing maintenance and application use of this information....

2009/07/13

This checklist centers on readying the organization for MDM and socializing the concepts that accompany a transition to centrally managed corporate information resources.

2009/07/13

This post will be the first in an ongoing series about data quality whitepapers that I have read and can endorse as worthy.

2009/07/13

I have seen that in their enthusiasm to implement software, people often ignore both explicit and subtle challenges that may hamper the strategic success of the program. There are risks in not fully considering how transitioning to a unified target data architecture could impact the way the business processes (and corresponding legacy applications) operate. To this end, we've started assembling a checklist that can be used to identify certain risk factors that may prevent the successful implementation of MDM. This month we begin this checklist, and I'll add to it over the next few months as well. For each checklist item, we provide some description and a number of questions....

2009/07/13

In Dante's Inferno, the words 'Abandon all hope, ye who enter here' are inscribed above the entrance into hell. The Roman poet Virgil was Dante's guide through its nine circles, each an allegory for unrepentant sins beyond forgiveness. The Very Model of a Modern DQ General will be your guide on this journey through nine of the most common mistakes that can doom your data quality project....

2009/07/12

The recent emphasis on regulatory compliance, SOA, and mergers and acquisitions has made the creating and maintaining of accurate and complete master data a business imperative. This paper covers the reasons for adopting master-data management, the process of developing a solution, and several options for the technological implementation of the solution. (12 printed pages)...

2009/07/08

Microsoft SQL Server 2008 R2 Master Data Services enables organizations to start with simple solutions for analytic or operational requirements, and then adapt the solutions to additional requirements incrementally. We support multiple uses of the same data....

2009/07/07

With Microsoft's recent announcement of Master Data Management offerings (the result of the 2007 Statature acquisition and some additional development), the MDM field takes two steps forward and presents the possibility that mid-market firms (and smaller) can begin to enjoy the benefits of handling data in a more unified, systematic way....

2009/06/26

If you've worked on a Master Data Management (MDM) project, specifically a Customer Data Integration (CDI) effort, you may think you're in a remake of 'What's My Line', but now it is called 'What's My Role.' Because we are trying to integrate customer data from possibly dozens of systems, we need to understand what role the customer played in that system....

2009/06/25

When an enterprise first encounters master data management, it often doesn't have a clear understanding of how MDM will affect the architecture of its business transaction systems or business intelligence systems. This article describes master data patterns in legacy system architectures, a general MDM architecture and some ways the new MDM layer affects the master data patterns in the legacy layers....

2009/06/17

Kalido delivers a robust, business model-driven, best practice-based information management engine that can automatically feed information to end users through their BI tools making them more productive far more quickly and reducing internal costs. Kalido's information management engine allows you to quickly model critical business scenarios such as organizational change or margin analysis, unlocking true intelligence about your business....

2009/06/17

Tool that enables model driven development of data warehouses and data marts.

2009/06/16

We've all heard about the importance of data quality in our IT systems and how the data that flows through our applications is the fuel of the business processes. Yet, surprisingly few organizations have a structured approach to measuring the quality of their data. Some may have a few custom reports or manually compiled Excel sheets that show a few aspects of data quality, but if information is truly an enterprise asset, shouldn't we be measuring and monitoring it like we do with all the other assets of the organization? Like most other things, data quality can only be managed properly if it is measured and monitored....

2009/06/16

By now, most organizations understand the concept of master data management (MDM). After all, vendors like IBM, Siperian and others have been pushing the MDM message for years. What most organizations don't understand, however, is how exactly to get the initiative under way, according to John Radcliffe, an analyst with Stamford, Conn.-based Gartner Inc....

2008/08/25

There are two kinds of organizations: those that have implemented a master data management (MDM) solution, and those that haven't but will in the near future. Despite where each organization may be in their MDM effort, what each have in common are questions about achieving better business processes. Fortunately, these companies can learn and benefit from the experiences of organizations that have pioneered MDM and organize their efforts around a common set of principles. For those organizations whose initial MDM efforts brought early success, the question is: how can the lessons learned be leveraged to drive more effective data governance across other lines of business and more elements of the system's infrastructure?...

2008/07/14

Without a sound description of the problems being solved, as well as clear communications around key decisions and the authority to make them, data governance can fail before it really begins.

2008/04/30

Data definitions are not word games. They are necessary for the effective utilization of information in enterprises. Context needs to be included as part of the conceptual framework within which data is administered. It is time to move away from simplisti...

2008/02/20

Organizations that aren't managing information as a resource are wasting as much as half their IT budgets "moving data from database A to database B." This troubling perspective, from expert Larry English, kicked off this week's TDWI World Conference in L...